Typical relational database management system (RDBMS) products have limitations with respect to providing users with specific views of data. Thus, front-ends have been developed for RDBMS products so that data retrieved from the RDBMS can be aggregated, summarized, consolidated, summed, viewed, and analyzed. This type of functionality is known as on-line analytical processing (OLAP).
OLAP is a key part of most data warehouse and business analysis systems. OLAP services provide for fast analysis of multidimensional information. OLAP services provide for multidimensional access and navigation of data in an intuitive and natural way, providing a global view of data that can be drilled down into particular data of interest. Speed and response time are important attributes of OLAP services that allow users to browse and analyze data online in an efficient manner.
Data in an OLAP system can be characterized in terms of its complexity, that is, the number of dimensions used to index the data. Thus, a complex data set is one that has many dimensions. Complex data sets have the advantage of flexibility in that users can submit more queries to complex data sets than to simple data sets. Accordingly, it is often desirable to use complex data sets. However, it is difficult to handle a large number of dimensions using conventional OLAP systems. Thus an improved mechanism for accessing a database in an OLAP system is desired.